Detecting tooth shade

ABSTRACT

Disclosed in a method, a user interface and a system for use in determining shade of a patient&#39;s tooth, wherein a digital 3D representation including shape data and texture data for the tooth is obtained. A tooth shade value for at least one point on the tooth is determined based on the texture data of the corresponding point of the digital 3D representation and on known texture values of one or more reference tooth shade values.

CROSS REFERENCE TO RELATED APPLICATIONS

The present application is a continuation of U.S. application Ser. No.16/946,186, filed on Jun. 9, 2020, which is a continuation of U.S.application Ser. No. 15/888,764, filed on Feb. 5, 2018, now U.S. Pat.No. 10,695,151, which is a continuation of U.S. application Ser. No.15/117,078, filed on Aug. 5, 2016, now U.S. Pat. No. 10,010,387, whichis a U.S. national stage of International Application No.PCT/EP2015/052537, filed on Feb. 6, 2015, which claims the benefit ofDanish Application No. PA 2014-70066, filed on Feb. 7, 2014. The entirecontents of each of U.S. application Ser. No. 16/946,186, U.S.application Ser. No. 15/888,764, U.S. application Ser. No. 15/117,078,International Application No. PCT/EP2015/052537, and Danish ApplicationNo. PA 2014-700665 are hereby incorporated herein by reference in theirentirety.

TECHNICAL FIELD

This invention generally relates to methods and a user interfaces fordetermining the shade of a patient's tooth or teeth and for utilizingthe determined tooth shades for designing and manufacturing dentalrestorations.

When designing and manufacturing a dental restoration for a patient,such as a crown or a bridge restoration, it is advantageous that boththe shape and shade of the manufactured restoration is adapted to thepatient's natural teeth surrounding the restoration. If the shade of therestoration differs significantly from the surrounding natural teeth,e.g. is significantly darker or brighter than these, the restorationappear artificial and deteriorate the aesthetic impression of thepatient's smile.

The tooth color can be represented in many different color spaces, suchas the L*C*h* color space representing color in terms of Lightness,Chroma and Hue, or in the L*a*b* color space as described e.g. by Hasselet al. (Hassel 2012) and Dozic et al. (Dozic 2007). The L*a*b* colorspace has the advantage that it is designed to approximate human visionwith the L* component closely matches human perception of lightness.

In order to aid dental technicians in their manual work of manufacturinga restoration which appears natural, the tooth colors are oftenexpressed in terms of reference tooth shade values of a tooth shadesystem (often referred to as a tooth shade guide). Each reference toothshade value in a tooth shade guide represents a predetermined and knowntooth color value and often correspond to the color of commerciallyavailable ceramics for the production of dental restorations. This ise.g. the case for the VITA 3D-Master or the VITA Classic shade guidesprovided by VITA Zahnfabrik, Germany.

In the VITA 3D-Master system, tooth shades are expressed in codesreferring to the L*C*h* color space, where each code is constructedaccording to (Lightness, hue, Chroma). One example of a tooth shadevalue is 3R1.5 where “3” refers to the lightness, “R” to the hue and“1.5” to the Chroma of the tooth. This allows the dentist to describethe shade of the patient's tooth in terms that a dental technicianimmediately understands, such that the technician will know from whichceramics he should manufacture the restoration to provide that it hasthe correct shade.

When manually determining which reference tooth shade value best matchesthe color of a patient's tooth, the dentist holds differentpre-manufactured teeth of the shade guide at the tooth for comparison.Often a picture is taken with the pre-manufactured structures arrangedat the teeth. The technician who produces the prosthetic then uses thepicture in evaluating which ceramic must be used for the different partsof the restoration based on the picture. This process is both timeconsuming and inaccurate.

SUMMARY

Disclosed is a method for determining shade of a patient's tooth,wherein the method comprises:

-   -   obtaining a digital 3D representation of the tooth, where the        digital 3D representation comprises shape data and texture data        for the tooth; and    -   determining a tooth shade value for at least one point on the        tooth based on the texture data of the corresponding point of        the digital 3D representation and on known texture values of one        or more reference tooth shade values.

Disclosed is a user interface for determining and displaying shade of apatient's tooth, wherein the user interface is configured for:

-   -   obtaining a digital 3D representation of the tooth, said digital        3D representation comprising shape data and texture data for the        tooth;    -   displaying at least the shape data of the digital 3D        representation such that the shape of the tooth is visualized in        the user interface;    -   determining a tooth shade value for at least one point on the        tooth based on the texture data of the corresponding point of        the digital 3D representation and on known texture values of one        or more reference tooth shade values; and    -   displaying the determined tooth shade value.

The texture data of the digital 3D representation expresses the textureof the tooth. The texture data can be a texture profile expressing thevariation in the texture over the tooth. The shape data of the digital3D representation expresses the shape of the tooth.

In some embodiments, the texture information comprises at least one oftooth color or surface roughness.

When the texture information comprises tooth color information, thetexture data expressing a texture profile of the tooth may be color dataexpressing a color profile of the tooth, and the tooth shade value for apoint on the tooth may be derived by comparing the color data of thecorresponding point of the digital 3D representation with known colorvalues of one or more reference tooth shade values.

Determining both the tooth shade value from a digital 3D representationcomprising both shape data expressing the shape of the tooth and texturedata expressing a texture profile of the tooth provides the advantagethat shade and geometry information are directly linked. This e.g.advantageous e.g. in CAD/CAM dentistry where dental restorations aredesigned using Computer Aided Design (CAD) tools and subsequentlymanufactured from the design using Computer Aided Design (CAM) tools.The material used for the manufacture of the dental restoration can thenbe selected based on the determined tooth shade value.

In many cases, the dental restoration is manufactured with a shadeprofile where the shade differs from the incisal edge towards cervicalend of the restoration. The disclosed invention allows the operator todetermine tooth shade values for several points on the tooth such that ashade profile can be determined for the dental restoration. Multi-shadedmilling blocks exits which mimics standard tooth shade profiles. Havingthe shape data and the tooth shade values linked via the digital 3Drepresentation provides that the correct portion of the multi-shadedmilling block can be milled out. The remaining portion of themulti-shaded milling block forming the dental restoration will then havea shape and shade profile which closely resembles that of a naturaltooth.

In some embodiments, obtaining the digital 3D representation of thetooth comprises recording a series of sub-scans of the tooth, where atleast one of said sub-scans comprises both texture information andgeometry information for said tooth, and generating the digital 3Drepresentation of the tooth from the recorded series of sub-scans.

When a plurality of the sub-scans comprise texture information, thetexture data for the digital 3D representation can be derived bycombining the texture information of the several sub-scans.

The recorded sub-scans comprise at least data of the tooth for which theshade is determined, but potentially also of the neighboring teeth suchthat for example the shape and location of the neighboring teeth can betaken into account when designing a dental restoration for the tooth.Texture information and texture data for the neighboring teeth can alsobe used to determine the shade value for the tooth, e.g. byinterpolation of the shades determined for the neighbor teeth.

In some embodiments, the method comprises creating a shade profile forthe tooth from shade values determined for one or more of points on thetooth.

The shade profile of natural teeth often has a brighter shade at theincisal edge of the tooth and gradually changes into a darker shadetowards the cervical end of the tooth, i.e. the end at the patient'sgingiva.

When the tooth shade value is determined for one point only the toothshade profile may be generated based on knowledge of the normal toothshade profile for that particular type of tooth and patient. Thisknowledge may relate to how the shade profile normally changes over thetooth, the age and gender of the patients, etc.

Often the profile will be based on tooth shades determined in severalpoints on the tooth to provide the most reliable tooth shade profile.

In some embodiments the user interface is configured for creating ashade profile for the tooth from tooth shade values determined for oneor more points on the tooth.

In some embodiments, the tooth shade profile can be created byinterpolation of tooth shade values determined for points distributedover the tooth surface with some distance between the points. The toothshade value for some parts of the tooth surface are then not deriveddirectly from sub-scan texture information relating to these parts butfrom the determined tooth shade values for other parts/points on thetooth surface. A tooth shade profile for the entire labial/buccalsurface of the tooth can thus be created from a selection of points onthe surface providing a fast and often sufficiently accurate procedurefor creating the tooth shade profile. The interpolation of the toothshade values can be realized by an interpolation in each of thecoordinates of the color space used to describe the tooth color.

In some embodiments, the tooth shade profile comprises a one or moretooth shade regions on the tooth surface where an average tooth shade isderived for each region from tooth shade values determined for a numberof points within the region.

The tooth shade region can be defined by a structure encircling aportion of the tooth surface in the digital 3D representation, whereeither the operator or a computer implemented algorithm decides whereeach geometric structure is located on the digital 3D representation.Different shapes (e.g. circles, squares, or rectangles) and sizes (e.g.corresponding to a few millimeters) of the geometric structure can beused. The number of points within the geometrical structure can beincreased to provide a more accurate measure of the shade or reduced toprovide a faster calculation.

The average tooth shade value for a region can e.g. be derived as aweighted average where the tooth shade value for points in the center ofthe structure is assigned a higher weight than tooth shade value ofpoints closer to the boundary.

The tooth surface can also be divided into a coronal, a middle and acervical region. Some natural teeth has a shade profile which can beexpressed by such a division and many dentists and dental techniciansare familiar with such a division

In some embodiments, tooth shade values are determined for a pluralityof teeth, i.e. on parts of the digital 3D representation correspondingto two or more teeth, and a tooth shade value and/or a tooth shadeprofile for each of these teeth is created from the determined toothshade values.

In some embodiments, the texture data at least partly are derived bycombining the texture information from corresponding parts of a numberof the sub-scans.

The digital 3D representation can be generated through registration ofsub-scans into a common coordinate system by matching overlappingsections of sub-scans, i.e. the sections of the sub-scans which relateto the same region of the tooth. When two or more sub-scans alsocomprise texture information relating to the same region of the tooth,deriving the texture data for this region in the digital 3Drepresentation can comprise combining the corresponding textureinformation, i.e. the texture information in the sub-scans correspondingto the same sections of the tooth.

Deriving the texture data based on texture information from two or moresub-scan can provide a more accurate measurement of the texture data.The texture information of one sub-scan for a particular region of thetooth may be unreliable e.g. due to the angle between the surface inthis region and the scanner when this particular sub-scan was recorded.The combination of texture information from several sub-scans canprovide a more reliable color.

In some embodiments, combining the texture information from thesub-scans comprises interpolating the texture information, i.e. textureinformation from parts of the sub-scans corresponding to a point on thetooth are interpolated to determine the texture data for that point.

Such an interpolation can provide that the determined texture data ismore accurate e.g. in cases where the texture information for a point onthe tooth is not linearly varying over the sub-scans such that a simpleaveraging will not provide the best result.

In some embodiments, combining the texture information from thesub-scans comprises calculating an average value of the textureinformation, i.e. texture data for a point on the digital 3Drepresentation are determined by averaging the texture information ofthe sub-scans corresponding to that point on the tooth.

In some embodiments, the calculated average value is a weighted averageof the texture information.

This approach has the advantage that the derived texture data of thedigital 3D representation are not as sensitive to errors in the textureinformation of a single sub-scan.

Such errors can be caused by several factors. One factor is the anglebetween the optical path of the probe light at the tooth surface and thetooth surface itself. When utilizing e.g. the focus scanning technique,the texture data for a point on the tooth is preferably derived from anumber of sub-scans where at least some of the sub-scans are recorded atdifferent orientations of the scanner relative to the teeth. Thesections of the sub-scans relating to this point are hence acquired atdifferent angles relative to the tooth surface in this point.

A portion of a sub-scan recorded from a surface perpendicular to theoptical path of the probe light at the tooth may be dominated byspecular reflected light which does not describe the texture of thetooth but rather the spectral distribution of the probe light. A portionof a sub-scan recorded from a tooth surface almost parallel to theoptical path is often quite weak and hence often provide an erroneousdetection of the texture at that point.

In some embodiments, the texture information from parts of a sub-scanrelating to a tooth surface which is substantially perpendicular orparallel to the optical path are assigned a low weight in the weightedaveraging of the texture information to determine the texture data forthe point.

The orientation of the scanner relative to the tooth when a sub-scan isacquired can be determined from the shape of the sub-scan. Parts of thesub-scan relating to tooth surfaces which are substantially parallel orperpendicular to the optical path can thus immediately be detected inthe sub-scan such that the texture information of the correspondingparts are assigned at low weight when determining the texture data forthis point from a series of sub-scans.

A specular reflection from the tooth often has an intensity which issignificantly higher than that of e.g. diffuse light from surfaces whichhave an oblique angle relative to the optical path. In some cases thespecular reflection will saturate the pixels of the image sensor usedfor the recording of the sub-scans.

In some embodiments, the method comprises detecting saturated pixels inthe recorded sub-scans and assigning a low weight to the textureinformation of the saturated pixels when combining the textureinformation from the sub-scans, i.e. when calculating the weightedaverage of the texture information.

Specular reflection from a tooth surface may also be detected from acomparison between the spectrum of the light received from the tooth andthat of the probe light. If these spectra a very similar it indicatesthat the tooth has a perfectly white surface which is not natural. Suchtexture information may thus be assigned a low weight in a weightedaverage of texture information.

In some embodiments determining the tooth shade value for the pointcomprises selecting the reference tooth shade value with known texturevalue closest to the texture data of the point.

When the texture data comprises color data, selecting the tooth shadevalue of the point can comprise calculating the color difference betweenthe determined color data in the point and the color data of thereference tooth shade values. This difference can e.g. be calculated asa Euclidian distance in the used color space. As an example, Dozic etal. (Dozic 2007) describes that the Euclidian distance ΔE between twopoints (L*₁, a*₁, b*₁) and (L*₂, a*₂, b*₂) in the L*a*b* color space isgiven by:

${\Delta E} = \sqrt[2]{\left( {L_{1}^{*} - L_{2}^{*}} \right)^{2} + \left( {a_{1}^{*} - a_{2}^{*}} \right)^{2} + \left( {b_{1}^{*} - b_{2}^{*}} \right)^{2}}$

Selecting the tooth shade value can then comprise determining for whichof the reference tooth shades the color difference, i.e. the Euclidiandistance, is the smallest.

In some embodiments determining the tooth shade value for the pointcomprises an interpolation of the two or more reference tooth shadevalues having known texture values close to the texture data of thepoint.

This interpolation provides that the tooth shade can be represented witha more detailed solution than what is provided by the tooth shadestandard used to describe the tooth shade. For instance when using aLightness-Hue-Chroma code a tooth shade value of 1.5M2.5 can bedetermined for the tooth by interpolation of Lightness values of 1 and2, and Chroma values of 2 and 3.

The tooth shade value can be displayed in a user interface e.g. togetherwith the digital 3D representation of the tooth. If the digital 3Drepresentation also contains parts relating to other teeth the toothshade value for the tooth is preferably displayed at the tooth, such asat the point of the for which the tooth shade value has been determined.

The tooth shade value can also be represented as a color mapped onto thedigital 3D representation.

When a dental restoration is designed based on the determined toothshade value this can provide a visualization of how the restoration willappear together with neighboring teeth also contained in the digital 3Drepresentation obtained by scanning the teeth.

In some embodiments, the method comprises deriving a certainty scoreexpressing the certainty of the determined tooth shade value.

Deriving a certainty score for the determined tooth shade value providesthe advantage that a measure of how accurate the determined value is canbe displayed to the operator, preferably when the patient is still atthe clinic such that further scanning can be performed if this isrequired to provide a more precise tooth shade value.

In some embodiments, the method comprises generating a visualrepresentation of the certainty score and displaying this visualrepresentation in a user interface.

In some embodiments, the method comprises generating a certainty scoreprofile at least for a portion of the tooth, where the certainty scopeprofile represents the certainty scores for tooth shade valuesdetermined for a number of points on the tooth, such as for the valuesin a tooth shade profile for the tooth. The certainty score profile canbe mapped onto the digital 3D representation of the tooth and visualizedin a user interface. When the tooth shade profile also is mapped ontothe tooth digital 3D representation the operator may be allowed totoggle between having the tooth shade profile and having the certaintyscope profiled visualized on the digital 3D representation.

In some embodiments the visual representation of the certainty score isdisplayed together with or is mapped onto the digital 3D representationof the tooth.

In some embodiments, the method comprises comparing the derivedcertainty score with a range of acceptable certainty score values. Thisis done to verify that the certainty score is acceptable, i.e. that thedetermined tooth shade value is sufficiently reliable.

One boundary of the range can be defined by a threshold value. When ahigh certainty scope indicates that the determined shade value mostlikely is correct, the threshold value may define the lower boundary ofthe range and vice versa.

A visual representation of the certainty score or of the result of thecomparison of the certainty score with the range can be generated anddisplayed in a user interface. Preferably, this visual representation isdisplayed together with the determined tooth shade value.

In some embodiments, the method comprises deciding based on thecertainty score whether the determined tooth shade value or tooth shadeprofile is acceptable. This may be based on the comparison of thederived certainty score and the range of acceptable certainty scorevalues, e.g. where it is decided that the determined tooth shade valueis acceptable if the certainty score is within the range of acceptablevalues.

In some embodiments, the certainty measure relates to how uniform thesub-scan texture information is at the point.

If large variations are found in the texture information in the vicinityof the parts corresponding to the point for a substantial fraction ofthe sub-scans, the texture data derived therefrom may be unreliable andthe tooth shade value derived for this point is accordingly not veryreliable.

In some embodiments, the certainty measure relates to how close thetexture data is to the known texture value of the determined tooth shadevalue. In particular, the certainty measure may relate to how close oneparameter of the color data of the digital 3D representation is to thecorresponding parameter of the known color for the determined toothshade value. For example, the certainty measure may relate to thedifference in the lightness parameter between point of the digital 3Drepresentation and the determined tooth shade value.

The Euclidian distance between the color data to the selected referencetooth shade value can also be used in determining the certainty measure.If the Euclidian distance is above a threshold value the uncertainty isthen evaluated to be too large. The color data can here both relate tocolor data of the point or the average color data for a regionsurrounding the point.

In some embodiments, the certainty measure relates to the amount oftexture information used to derive the texture data at the point.

When the texture data for the point is derived from a limited amount oftexture information the texture data, and accordingly the tooth shadevalue derived therefrom, may be less reliable than the tooth shadevalues derived from large amounts of texture information.

In some embodiments, the visual representation of the certainty scorecomprises a binary code, such as red for certainty scores outside arange of acceptable certainty score values, and green for certaintyscores within the range, a bar structure with a color gradient, anumerical value, and/or a comparison between the texture data and theknown texture value of the determined tooth shade value.

In some embodiments, the visual representation of the certainty scorecomprises a certainty score indicator.

The certainty score indicator may comprise a bar structure with a colorgradient going from a first color representing a low certainty score toa second color representing a high certainty score. The first color maybe red and the second color green. The color gradient of the barstructure may be configured to have an intermediate color, e.g. yellowrepresenting the threshold value for the certainty score. The certaintyscore indicator may comprise marker which is arranged relative to thecolor gradient of the bar structure such that it indicated the certaintyscore.

In some embodiments, the visual representation of the certainty scorecomprises a numerical value, such as a numerical value in an intervalextending from a lower limit indicating a low certainly, i.e. arelatively uncertain tooth shade value, to a higher limit indicating ahigh certainty, i.e. a relatively certain tooth shade value.

In some embodiments, the one or more reference tooth shade values relateto shade values for natural teeth with intact surface and/or to shadevalues for teeth prepared for a dental restoration.

The reference tooth shade values used for determining the tooth shadecan be selected based on the tooth. Intact and healthy teeth normallyhave tooth shades in one range of tooth shade values where a toothprepared for a dental restoration has a tooth shade in another range,which may overlap with the range for healthy teeth. It may thus beadvantageous that the operator enters whether the tooth is intact orprepared for a restoration and the appropriate color space is used inthe comparison with the texture data.

If the color data in the point on the digital 3D representation of thetooth has a poor match to all the reference tooth shade values of theselected tooth shade system/guide the point may e.g. be on the gingivaof the patient or relate to silver filling.

In some embodiments, the method comprises comparing the texture datawith known texture values for soft oral tissue, such as gum tissue andgingiva.

This may e.g. be relevant when the certainty scores are outside saidrange of acceptable certainty score values for all tooth shade values ofa tooth shade system, i.e. if there is a poor match between the texturedata and the known texture for all the tooth shades of the referenceset.

In a user interface for implementing the method, it may be suggested tothe operator that the point perhaps is not on a tooth surface but on thegums or gingiva of the patient. This suggestion may be provided bothwhen the texture data has been found to give a good match with knowntexture values of gum/gingiva and/or when the texture data has a poormatch with the known texture values of the reference tooth shade valuesin the tooth shade system or systems.

In some embodiments, the method comprises determining an alternativetooth shade value for the point when said certainty score is outsidesaid range of acceptable certainty score values.

In some embodiments, the method comprises displaying the alternativetooth shade value in the user interface optionally together with thedigital 3D representation of the patient's set of teeth and/or theinitially determined tooth shade value

The digital 3D representation of the tooth is generated at least partlyfrom the geometry information of the sub-scans. In some embodiments, thetexture information of the sub-scans is also taken into account whengenerating the digital 3D representation of the tooth.

Sub-scans comprising texture information and geometry information may berecorded for more than said tooth, such that the generated digital 3Drepresentation may comprise shade data expressing the shape and texturedata expressing the texture profile of several of the patient's teeth.

Disclosed is a method for determining shade of a patient's tooth,wherein the method comprises:

-   -   recording a series of sub-scans of the patient's set of teeth,        where a plurality of said sub-scans comprises both texture        information and geometry information for said tooth;    -   generating a digital 3D representation of the tooth from said        sub-scans, wherein the digital 3D representation comprises shape        data expressing the shape of the tooth and texture data        expressing a texture profile of the tooth; and    -   determining a tooth shade value for a point on the tooth by        comparing the texture data of the corresponding point of the        digital 3D representation with a known texture value of one or        more reference tooth shade values.

Disclosed is a user interface for determining and displaying shade of apatient's tooth, wherein the user interface is configured for:

-   -   obtaining a digital 3D representation of the tooth, said digital        3D representation comprising shape data expressing the shape of        the tooth and texture data expressing a texture profile of the        tooth;    -   displaying at least the shape data of the digital 3D        representation such that the shape of the tooth is visualized in        the user interface;    -   determining a tooth shade value for a point on the tooth by        comparing the texture data of the corresponding point of the        digital 3D representation with a known texture value of one or        more reference tooth shade values; and    -   displaying the determined tooth shade value.

In some embodiments, the user interface is configured for deriving acertainty score expressing the certainty of the determined tooth shadevalue for said point.

In some embodiments, the user interface comprises a virtual tool whichwhen activated on a point of the digital 3D representation of the toothprovides that

-   -   the determined tooth shade value for the point; and/or    -   a visual representation of a certainty score for the determined        tooth shade value; and/or    -   a visual representation of a comparison of the derived certainty        score with a range of acceptable certainty score values        is visualized in the user interface.

The user interface can then provide the operator with an opportunity todecide based on the visualized certainty score and/or the visualrepresentations whether the determined tooth shade value or tooth shadeprofile is acceptable.

In some embodiments, the visual representation of the comparison of thederived certainty score with the range of acceptable certainty scorevalues comprises a binary code, such as red for certainty scores outsidea range of acceptable certainty score values, and green for certaintyscores within the range. Other means for this visualization aredescribed above.

The visualized certainty score and/or the representation(s) of thecertainty score or comparison of the certainty score with the range ofacceptable certainty score values may be displayed at the digital 3Drepresentation in the user interface or in a shade value region of theuser interface.

In some embodiments, the user interface is configured for determining analternative shade value for the point and for displaying the alternativeshade value when the certainty scores outside a range of acceptablecertainty score values.

Disclosed is a method for designing a dental restoration for a patient,wherein the method comprises:

-   -   obtaining a digital 3D representation of at least one tooth,        said digital 3D representation comprising shape data expressing        the shape of the tooth and texture data expressing a texture        profile of the tooth;    -   determining a tooth shade value for a point on the tooth by        comparing the texture data of the corresponding point of the        digital 3D representation with a known texture value of one or        more reference tooth shade values; and    -   creating a digital restoration design for one or more of the        patient's teeth; and    -   selecting a restoration shade of the digital restoration design        based on said tooth shade value.

The digital restoration design can e.g. be for the manufacture of dentalprosthetic restoration for the patient, such as a crown or a bridgerestoration, where the digital restoration design expresses a desiredshape and shade profile of the dental restoration. Such digitalrestoration designs can be in the form of a CAD model of the dentalrestoration.

In some embodiments, the method comprises suggesting a dental materialfor manufacturing the dental restoration from the digital restorationdesign based on the determined restoration shade.

In cases where the dental restoration is designed and manufactured foran existing tooth which has an acceptable shade, the tooth shade valueor tooth shade profile can be determined for the existing tooth and theshade of the digital restoration design based on the tooth shade valueor tooth shade profile of the existing tooth.

This may e.g. be advantageous for the crown portions of a bridgerestoration in the case where the tooth which is intended to accept thecrown portion of the bridge is a healthy tooth.

In some cases the dental restoration is designed and manufactured for atooth which either is damaged or has an undesired shade profile, such asfor a broken or dead tooth. In such cases it can be advantageous todetermine the tooth shade value or tooth shade profile for one or moreof the neighboring teeth and selecting the restoration shade of thedigital restoration design from e.g. an interpolation of the tooth shadevalues/profiles of the neighboring teeth.

Disclosed is a method for designing a dental restoration for a firsttooth, wherein the method comprises:

-   -   obtaining a digital 3D representation of the patient's set of        teeth, said digital 3D representation comprising shape data and        texture data expressing the shape and texture profile,        respectively, of at least one second tooth;    -   designing a digital restoration design for the first tooth;    -   deriving a desired texture profile of the digital restoration        design from the texture data of the at least one second tooth;        and    -   determining a restoration shade value or restoration shade        profile of the digital restoration design by comparing the        desired texture profile with texture values for one or more        reference tooth shade values.

In some embodiments, the desired texture profile is derived byinterpolation or averaging of the texture data of the digital 3Drepresentation of the neighbor teeth.

In some embodiments, one or more of the sub-scans comprise textureinformation for the patient's soft tissue, and optionally geometryinformation for said soft tissue. The generated digital 3Drepresentation may then comprise shape data expressing the shape of thesoft tissue and texture data expressing a texture profile of the softtissue.

From this information, an aesthetica) pleasing denture can be designedwhere the color of the soft tissue part of the denture is selected basedon the texture profile of the corresponding part of the digital 3Drepresentation.

Knowledge of the texture of the soft tissue, such as of the color of thesoft tissue, can also be used for diagnostics. When the texture data ofa point on the digital 3D representation corresponding to soft tissuedoes not provide a sufficiently good match with a known range of texturevalues for soft tissue, a warning may be prompted in a user interface toalert the operator that the soft tissue is suspicious.

Disclosed is a system for determining shade of a patient's tooth,wherein the system comprises:

-   -   a scanner capable of recording a digital 3D representation of        the tooth, where the digital 3D representation comprises shape        data and texture data for the tooth; and    -   a data processing system comprising a computer-readable medium        having stored thereon the program code means for causing the        data processing system to determine a tooth shade value for at        least one point on the tooth based on the texture data of the        corresponding point of the digital 3D representation and on        known texture values of one or more reference tooth shade values        using the method according to any of the embodiments.

In some embodiments, the sub-scans are recorded using an intra-oralscanner, such as the 3Shape TRIOS intra-oral scanner.

The intra-oral scanner may be configured for utilizing focus scanning,where the sub-scans of the scanned teeth are reconstructed from in-focusimages acquired at different focus depths. The focus scanning techniquecan be performed by generating a probe light and transmitting this probelight towards the set of teeth such that at least a part of the set ofteeth is illuminated. Light returning from the set of teeth istransmitted towards a camera and imaged onto an image sensor in thecamera by means of an optical system, where the image sensor/cameracomprises an array of sensor elements. The position of the focus planeon/relative to the set of teeth is varied by means of focusing opticswhile images are obtained from/by means of said array of sensorelements. Based on the images, the in-focus position(s) of each of aplurality of the sensor elements or each of a plurality of groups of thesensor elements may be determined for a sequence of focus planepositions.

The in-focus position can e.g. be calculated by determining the maximumof a correlation measure for each of a plurality of the sensor elementsor each of a plurality of groups of the sensor elements for a range offocus planes as described in WO2010145669. From the in-focus positions,sub-scans of the set of teeth can be derived with geometry informationrelating to the shape of the scanned surface. When e.g. the image sensoris a color sensor and the light source provides a multispectral signal aplurality of the sub-scans can include both geometry information andtexture information, such as color information, for said tooth.

A digital 3D representation of the set of teeth can then be generatedfrom the recorded sub-scans by e.g. the use of an Iterative ClosestPoint (ICP) algorithm. Iterative Closest Point (ICP) is an algorithmemployed to minimize the difference between two clouds of points. ICPcan be used to reconstruct 2D or 3D surfaces from different scans orsub-scans. The algorithm is conceptually simple and is commonly used inreal-time. It iteratively revises the transformation, i.e. translationand rotation, needed to minimize the distance between the points of tworaw scans or sub-scans. The inputs are: points from two raw scans orsub-scans, initial estimation of the transformation, criteria forstopping the iteration. The output is: refined transformation.Essentially the algorithm steps are:

-   -   1. Associate points by the nearest neighbor criteria.    -   2. Estimate transformation parameters using a mean square cost        function.    -   3. Transform the points using the estimated parameters.    -   4. Iterate, i.e. re-associate the points and so on.

The generated digital 3D representation formed by such a procedurecomprises shape data expressing the shape of the tooth. The textureinformation of the sub-scans can be used in various ways to provide thatthe generated digital 3D representation also comprises texture dataexpressing a texture profile of the tooth. For a number of thesub-scans, the part of the sub-scan relating to the same point on thetooth can be identified, e.g. during the ICP procedure. Thecorresponding texture information of these parts of the sub-scans canthen be combined to provide the texture data for that point.

Furthermore, the invention relates to a computer program productcomprising program code means for causing a data processing system toperform the method according to any of the embodiments, when saidprogram code means are executed on the data processing system, and acomputer program product, comprising a computer-readable medium havingstored there on the program code means.

The present invention relates to different aspects including the methodand user interface described above and in the following, andcorresponding methods and user interface, each yielding one or more ofthe described advantage, and each having one or more embodimentscorresponding to the embodiments described above and/or disclosed in theappended claims.

BRIEF DESCRIPTION OF THE DRAWINGS

The above and/or additional objects, features and advantages of thepresent invention, will be further elucidated by the followingillustrative and non-limiting detailed description of embodiments of thepresent invention, with reference to the appended drawings, wherein:

FIG. 1 shows an example of a flow chart for an embodiment.

FIGS. 2 to 4 show parts of screen shots of user interfaces.

FIG. 5 shows steps of a method for designing a dental restoration.

FIG. 6 shows a schematic of a system for determining tooth shade values

FIGS. 7A-7D and 8A-8B show schematics of intra-oral scanning.

FIGS. 9A-9B illustrates one way of determining tooth shade values fromtexture data.

DETAILED DESCRIPTION

In the following description, reference is made to the accompanyingfigures, which show by way of illustration how the invention may bepracticed.

FIG. 1 shows an example of a flow chart 100 for an embodiment of themethod for determining shade of a patient's tooth.

In step 102 a series of sub-scans of the patient's set of teeth isrecorded, where a plurality of said sub-scans comprises both textureinformation and shape information for the tooth.

In step 103 a digital 3D representation of the tooth is generated fromsaid sub-scans, where the digital 3D representation comprises texturedata expressing a texture profile of the tooth. The digital 3Drepresentation further comprises shape data expressing the shape of thetooth such that the shape of the tooth can be visualized in a userinterface.

In step 104 a tooth shade value for a point on the tooth is determinedbased on the texture data. This is done at least in part by comparingthe texture data of the corresponding point of the digital 3Drepresentation with a known texture value of one or more reference toothshade values. The reference tooth shade values may be provided in theform of a library file and comprise tooth shade values and correspondingtexture values based on e.g. the VITA 3D-Master and/or the VITA Classictooth shade systems.

FIGS. 2 to 4 show parts of screen shots from user interfaces in whichderived tooth shade values and visual representation of thecorresponding certainty scores for a number of tooth regions aredisplayed at the digital 3D representations of the patient's set ofteeth.

The point or points on the tooth for which the tooth shade value(s)is/are determined can be selected by an operator. This can be the casee.g. when the digital 3D representation of the tooth is visualized in auser interface and the operator uses a pointing tool, such as a computermouse, to indicate where on the digital 3D representation of the tooth,he wishes to determine the tooth shade value. The point or points canalso be selected by a computer implemented algorithm based onpredetermined positions on the digital 3D representation of the tooth,such as a point arranged at a certain distance to the incisal edge ofthe tooth.

The screen shot 210 seen in FIG. 2 shows three regions 212, 213, 214 onthe digital 3D representation of the patient's set of teeth. Two ofthese 212, 213, are selected at the part of the digital 3Drepresentation corresponding to the tooth 211 while the third 214 isselected on the soft tissue part 215 of the digital 3D representation.Average tooth shade value for a region can be calculated by averagingover tooth shade values derived for a number of points within the regionor by calculating an average texture value for the region anddetermining the average tooth shade value therefrom. The average toothshade values are displayed in tooth value sections 217, 218, 219 linkedto the regions in the user interface. In the tooth value sections 217,218 relating to the regions 212, 213 two tooth shade values aredisplayed where the upper shade value is derived using known texturevalues corresponding to the reference tooth shade values of the VITA3D-Master tooth shade system and the lower tooth shade values relates tothe VITA Classic tooth shade system. It is also seen that for the region213 closest to the gingiva, the tooth shade is determined to be 2L1.5 inthe VITA 3D-Master system and B1 in the VITA Classic system. In FIG. 2the certainty scores for the derived tooth shade values are visualizedas a certainty score indicator displayed next to the tooth shade values.In FIG. 2 the visualization of the certainty score indicator is in theform of a checkmark which indicates that the certainty score issufficiently good to provide that the derived tooth shade values can berelied upon. The color of the checkmark may provide further informationto the certainty score, such as in cases where a green checkmarkindicates a more certain tooth shade value than a yellow checkmark. Thethird region 214 is located at the patient's soft tissue. An anatomicalcorrect tooth shade value can hence not be calculated from the texturedata of that part of the digital 3D representation of the patient'steeth and the corresponding certainty scope is accordingly very low. Thevisualization of the certainty score in the tooth value section 219 ishence a cross indicating that the derived shade value was rejected.Further no shade value is indicated in the tooth value section 219.

The screen shot 310 seen in FIG. 3 shows two regions 312, 314 on thedigital 3D representation of the patient's set of teeth. One of theseregions 312 is selected at the part of the digital 3D representationcorresponding to the tooth 311 while the second region 314 is selectedon the soft tissue part 315 of the digital 3D representation. Averagetooth shade value for a region can be calculated as described above inrelation to FIG. 2. Shade value sections 317, 319 are also displayed forthe regions 312, 314. Two tooth shade values 321 are derived for theregion 312 and displayed in the corresponding tooth value section 317,where the upper value is derived using known texture valuescorresponding to the reference tooth shade values of the VITA 3D-Mastertooth shade system (derived tooth shade value is 1.5M1) and the lowervalue using the VITA Classic tooth shade system (derived tooth shadevalue is B1). In FIG. 3 the certainty score is visualized in the form ofa certainty score indicator 322 comprising a vertical bar with a colorgradient going from red representing a poor certainty score to greenrepresenting a good certainty score. The certainty score indicator has amarker indicating the certainty score on the bar. It is seen that thetooth shade value 1.5M1 of the VITA 3D-Master system is more certainthan the tooth shade value B1 of the VITA Classic system for thisregion. The tooth shade value of 1.5M1 is found by interpolation of thereference tooth shades 1M1 and 2M2.

The second region 314 is located at the patient's soft tissue. Ananatomical correct tooth shade value can hence not be calculated fromthe texture data of that part of the digital 3D representation of thepatient's teeth and the corresponding certainty scope is accordinglyvery low as seen in the vertical bars of tooth value section 319.

FIG. 4 shows a screen shot 410 where determined tooth shade values arederived for a total of 15 regions on the digital 3D representation ofthe tooth 411. The tooth shade values are all derived based on the knowntexture values of the reference tooth shade values of the VITA 3D-Mastertooth shade system. The certainty scores are visualized in the form of acertainty score indicator comprising a vertical bar with a colorgradient going from red representing a poor certainty score to greenrepresenting a good certainty score. As can be seen in the tooth valuesections 417, 418 of the user interface there are large variations inthe certainty scores. For example, the certainty score for the region412 is almost at maximum while the certainty score of the region 413 ismuch close to a threshold for acceptable certainty score values. Whentooth shade values are determined for a number of points on the tooth,the points may be arranged in a grid over the part of the digital 3Drepresentation of the tooth.

FIG. 5 shows steps of a method for designing a dental restoration.

In step 531 a digital restoration design is created e.g. based on theshape data of a digital 3D representation of the patient's set of teethand/or on template digital restoration design loaded from a library.Template digital restoration designs may e.g. be used when the tooth isbroken.

In step 532 the tooth shade values of different points or regions of theteeth are derived from the texture data of the digital 3D representationof the patient's set of teeth. From the derived tooth shade values orfrom tooth shade profiles created based on the derived tooth shadevalues a desired shade profile for the dental restoration can bedetermined. This can be based on e.g. feature extraction where shadevalues are extracted from the other teeth by e.g. identifying shadezones on these teeth and copying these zones to the dental restoration.It can also be based on established shade rules for teeth, e.g. a ruledescribing a relation between the tooth shades values or profiles of thecanines and the anterior teeth.

In step 533 the desired tooth shade value(s) for the dental restorationis merged into the digital restoration design.

When the dental restoration is to be drilled from a multicolored millingblock it is important that the dental restoration is milled from thecorrect parts of the milling block. In step 534 a CAD model of themilling block is provided, where the CAD model comprises information ofthe shade profile of the milling block material. The optimal position ofthe digital restoration design relative to the CAD model of the millingblock is then determined in 535, where different criteria can be applyto provide the best fit between the desired shade profile and whatactually can be obtained as dictated by the shade profile of the millingblock.

In step 536 the dental restoration is manufactured from the millingblock by removing milling block material until the dental restoration isshaped according to the digital restoration design.

FIG. 6 shows a schematic of a system for determining tooth shade values.The system 640 comprises a computer device 642 comprising a computerreadable medium 643 and a processor 644. The system further comprises avisual display unit 647, a computer keyboard 645 and a computer mouse646 for entering data and activating virtual buttons in a user interfacevisualized on the visual display unit 647. The visual display unit canbe a computer screen. The computer device 642 is capable of receiving adigital 3D representation of the patient's set of teeth from a scanningdevice 641, such as the TRIOS intra-oral color scanner manufactured by 3shape A/S, or capable of receiving scan data from such a scanning deviceand forming a digital 3D representation of the patient's set of teethbased on such scan data. The obtained digital 3D representation can bestored in the computer readable medium 643 and provided to the processor644. The processor is configured for implementing the method accordingto any of the embodiments. This may involve presenting one or moreoptions to the operator, such as where to derive the tooth shade valueand whether to accept a derived tooth shade value. The options can bepresented in the user interface visualized on the visual display unit647.

Many scanning devices have Bayer color filters with Red, Green and Bluefilters and hence record color information in the RGB color space. Forinstance a focus scanner can record series of 2D color images for thegeneration of sub-scans, where the color information is provided in theRGB color space. The processor 644 then comprises algorithms fortransforming the recorded color data into e.g. the L*a*b or L*C*h colorspaces.

The system may further comprise a unit 648 for transmitting a digitalrestoration design and a CAD model of a milling block to e.g. a computeraided manufacturing (CAM) device 649 for manufacturing a shaded dentalrestoration or to another computer system e.g. located at a millingcenter where the dental restoration is manufactured. The unit fortransmitting the digital restoration design can be a wired or a wirelessconnection.

The scanning of the patient's set of teeth using the scanning device 641can be performed at a dentist while deriving the tooth shade values canbe performed at a dental laboratory. In such cases the digital 3Drepresentation of the patient's set of teeth can be provided via aninternet connection between the dentist and the dental laboratory.

FIGS. 7A-7D and 8A-8B show schematics of intra-oral scanning.

Different scanner configurations can be used to acquire sub-scanscomprising both shape and texture information. In some scanner designsthe scanner is mounted on axes with encoders which provides that thesub-scans acquired from different orientations can be combined usingposition and orientation readings from the encoders. When the scanneroperates by the focus-scanning technique the individual sub-scans of thetooth are derived from a sequence of 2D images obtained while scanning afocus plane over a portion of the tooth. The focus scanning technique isdescribed in detail in WO2010145669. The shape information of thesub-scans for an object, such as a tooth, can be combined by algorithmsfor stitching and registration as widely known in the literature.Texture data relating to the tooth color can be obtained using a scannerhaving a multi-chromatic light source, e.g. a white light source and acolor image sensor. Color information from multiple sub-scans can beinterpolated and averaged by methods such as texture weaving, or bysimply averaging corresponding color components of the sub-scanscorresponding to the same point/location on the surface. Texture weavingis described by e.g. Callieri M, Cignoni P, Scopigno R. “Reconstructingtextured meshes from multiple range rgb maps”. VMV 2002, Erlangen, Nov.20-22, 2002.

In FIG. 7A the scanner 741 (here represented by a cross-sectional viewof the scanner tip) is held in one position relative to the teeth 711,760 (also represented by a cross-sectional view) while recording asequence of 2D images for one sub-scan. The illustrated teeth can e.g.be the anterior teeth in the lower jaw. The size of the Field of View(here represented by the full line 761 on the teeth) of the scanner isdetermined by the light source, the optical components and the imagesensor of the scanner. In the illustrated example, the Field of View 761covers part of the surface of the tooth 711 and part of the surface ofthe neighbor tooth 760. The generated digital 3D representation can thusalso contain data for the neighbor teeth. This is often advantageous,e.g. when the generated digital 3D representation is used for creating adigital restoration design for the manufacture of a dental restorationfor the tooth. In the Figure, the scanner is arranged such that theacquired sub-scan comprises shape and color information for the incisaledge 762 of the teeth. The probe light rays 763 from the scannercorresponding to the perimeter of the Field of View are also shown inthe Figure. These probe light rays 763 define the optical path 764 ofthe scanner probe light at the tooth 711.

A digital 3D representation of the tooth can be generated by combiningsub-scans acquired from different orientations relative to the teeth,e.g. by sub-scan registration. Sub-scans acquired from three suchdifferent orientations are illustrated in FIGS. 7B, 7C and 7D, whereonly the optical path 763 of the scanner probe light is used torepresent the relative scanner/tooth orientation in FIGS. 7C and 7D. Thesub-scans (here represented by the full line 765 on the teeth) coversdifferent but overlapping sections of the tooth surface such that thesub-scans can be combined by registration into a common coordinatesystem using e.g. an Iterative Closest Point (ICP) algorithm asdescribed above. A segment of each of the sub-scans corresponds to thepoint P on the tooth surface. When the sub-scans are registered togenerate a digital 3D representation of the tooth, a correlation betweenthese segments is established and the texture information of thesesub-scan segments can be combined to determine the texture data forpoint P on the generated digital 3D representation of the tooth.

One way of doing this is to calculate the average value for each of theparameters used to describe the texture. For example, when the L*a*b*color system is used to describe the color information provided in eachsub-scan, the color data of the digital 3D representation can be derivedby averaging over each of the L*, a*, and b* parameters of thesub-scans. For example, the L* parameter of the color data for a givenpoint P is then given by L

$(P) = {\frac{1}{N}\Sigma_{i}^{N}}$

L*_(i) (P) where N is the number of sub-scans used in deriving thetexture data and L*_(i) (P) is the L* parameter of the i′th sub-scan forthe segment relating to P. Equivalent expressions are true for the a*and b* parameters for point P. The color parameters for each point onthe digital 3D representation of the tooth can be determined forsections of or the entire surface of the tooth, such that the generateddigital 3D representation comprises both shape and texture informationabout the tooth. The spatial resolution of the color data does notnecessarily have to be identical to the resolution of the shape data ofthe digital 3D representation. The point P can be described e.g. inCartesian, cylindrical or polar coordinates.

When the color data is derived for a point on the tooth, the tooth shadevalue for that point can be determined by comparing the derived colordata with the known color data of the reference tooth shade values of atooth shade guide such as the VITA 3D-Master.

FIG. 8A-8B illustrates some potentially problematic tooth surface areasfor particular arrangements of the scanner 841 relative to the tooth811.

FIG. 8A shows two points P_(i) and P_(ii) on the tooth 811 where thetooth surface is either substantially perpendicular or parallel to theoptical path, such that the texture information recorded at P_(i) andP_(ii) may be unreliable. This is because the tooth surface at P_(i) isperpendicular to the optical path 864 i at point P_(i) which introducesthe risk of having specular reflections of the probe light. The opticalpath 864 ii at point P_(ii) is parallel to the tooth surface at P_(ii)such that the signal recorded from this part of the tooth surface inthis sub-scan is relatively weak. This may cause that the colorinformation in this section of the sub-scan are unreliable.

In order to obtain more precise color data the averaging of the colorinformation described above in relation to FIG. 7 can be a weightedaveraging where the color information of unreliable sub-scans segmentsare assigned a lower weight than others.

In FIG. 8B is indicated three different optical paths 864 i, 864 ii and864 iii at which sub-scans are acquired. When combining the colorinformation for point P the color information of the segments of thesub-scans recorded with optical paths 864 i and 864 ii should be given alower weight that the color information of the segment of the sub-scanrecorded with the optical path 864 iii.

This can be expressed by a modification of the equation given above. Fora weighted averaging of the color information, the L* parameter of thecolor data for a given point P is given by L*(P)=Σ_(i)^(N){α_(i)(P)·L*_(i)(P)}/Σ_(i) ^(N) α_(i) where α_(i) (P) is the weightfactor for the color information of the i′th sub-scan in the segment atP. When a given sub-scan (e.g. the j′th sub-scan) is recorded at anangle relative to the tooth surface which causes the optical path to bee.g. perpendicular to the tooth surface at P, the corresponding weightfactor α_(i)(P) is given a lower value than the color data of sub-scansacquired with an oblique angle between the optical path and the toothsurface.

Equivalent equations are true for the a* and b* parameters of the colordata for point P.

FIG. 9A=9B illustrates how a tooth shade value for a point P on a toothcan be determined based on reference tooth shade values.

For a given point P on the digital 3D representation, the color data(L*_(p)a*_(p), b*_(p)) has been determined, e.g. by combining the colorinformation of a series of sub-scans used for generating the digital 3Drepresentation. If the color information originally is recorded usingthe RGB color space it is transformed into the L*a*b* color space usingalgorithms known to the skilled person.

In the example illustrated by FIG. 9A, the color data of the digital 3Drepresentation and the known color values of the reference tooth shadesare expressed in the L*a*b* color space, and the reference tooth shadesare those from the VITA classical shade guide.

The reference shade values of the Vita classical shade guide are: B1,A1, B2, D2, A2, C1, C2, D4, A3, D3, B3, A3.5, B4, C3, A4, and C4. Thecolor data of these reference shades can be provided by scanning thecorresponding pre-manufactured teeth of the shade guide. These colordata are then also initially obtained in the RGB color space and can beconverted to the L*a*b color space using the same algorithms applied tothe color information/data for the point P.

The tooth shade value for the point is determined as the reference toothshade value which has the smallest Euclidian distance to the point inthe L*a*b color space. The Euclidian distance ΔE_(p−Ri) from the color(L*_(p), a*_(p), b*_(p)) to the known colors of the reference toothshade values are calculated using the expression:

${\Delta E_{P - {Ri}}} = \sqrt[2]{\left( {L_{P}^{*} - L_{Ri}^{*}} \right)^{2} + \left( {a_{P}^{*} - a_{Ri}^{*}} \right)^{2} + \left( {b_{P}^{*} - b_{Ri}^{*}} \right)^{2}}$

where Ri refers to the i′th reference tooth shade.

In FIG. 9A only the known colors (L*_(R1), a*_(R1), b*_(R1)) and(L*_(R2), a*_(R2), b*_(R2)) for the two closest reference values R1 andR2, respectively, are illustrated for simplicity. It can be seen thatthe Euclidian distance in the color space from P to R2 is the smallest,and the tooth shade in point P is hence selected as that of R2.

The certainty score for the tooth shade value determined for point Pdepends on how close the color data of the point P is to the known colorvalue of the selected reference tooth shade value. This can bequantified by the Euclidian distance and since point P is notparticularly close to R2 in FIG. 9A the determined tooth shade has apoor certainty value.

An alternative approach to using the Euclidian distance is to determineindividual parameters of the tooth shade value one at a time. Thisapproach can be used e.g. when the reference tooth shades values arethose of the Vita 3D-master system.

The reference tooth shade values of the Vita 3D-master shade guide areexpressed in codes consisting of the three parametersLightness-hue-Chroma, where Lightness is given in values between 1 and5, the Chroma in values between 1 and 3, and the hue as one of “L”,

“M”, or “R”. A shade code in the Vita 3D-master can e.g. be 2M1, wherethe Lightness parameter equals 2, the Chroma 1 and the hue “M”.

The known color data of the VITA 3D-master shade guide reference shadescan be provided by scanning the pre-manufactured teeth of the shadeguide. These color data are then also initially obtained in the RGBcolor space and can be converted to the L*a*b color space using the samealgorithms applied to the color information/data for the point P. Theknown color data of each reference shade guide (having a code expressedin terms of Lightness, hue and Chroma) is then provided in terms of theL*a*b color space.

Since the lightness L has the largest impact on the human perception ofthe tooth color, the value of the Lightness-parameter L*_(p) in thepoint is determined first. The value of L*_(p) is compared with thevalues of the L* parameters for the reference tooth shades. If L*_(p) isclose to the L*-value for the i′th reference tooth shade value, L*_(Ri)the L* parameter for point P may be set equal to L*_(Ri).

In some cases the Lightness parameter is not close to any of thereferences but instead is located almost in the middle between twoL*-values. For example when L*_(p) in the point is between the values ofL*_(Ri)=2 and L*_(Ri+1)=3 with almost equal distance to each of these asillustrated in FIG. 9B. Since the L*a*b color space is a linear space,the individual parameters of the shade values can be interpolated suchthat the Lightness for point P, L*_(p), can be set to 2.5.

The same procedure is performed for first the Chroma parameter andfinally for the hue such that the three parameter of the tooth shadevalue are determined.

Although some embodiments have been described and shown in detail, theinvention is not restricted to them, but may also be embodied in otherways within the scope of the subject matter defined in the followingclaims. In particular, it is to be understood that other embodiments maybe utilized and structural and functional modifications may be madewithout departing from the scope of the present invention.

In device claims enumerating several means, several of these means canbe embodied by one and the same item of hardware. The mere fact thatcertain measures are recited in mutually different dependent claims ordescribed in different embodiments does not indicate that a combinationof these measures cannot be used to advantage.

A claim may refer to any of the preceding claims, and “any” isunderstood to mean “any one or more” of the preceding claims.

It should be emphasized that the term “comprises/comprising” when usedin this specification is taken to specify the presence of statedfeatures, integers, steps or components but does not preclude thepresence or addition of one or more other features, integers, steps,components or groups thereof.

The features of the method described above and in the following may beimplemented in software and carried out on a data processing system orother processing means caused by the execution of computer-executableinstructions. The instructions may be program code means loaded in amemory, such as a RAM, from a storage medium or from another computervia a computer network. Alternatively, the described features may beimplemented by hardwired circuitry instead of software or in combinationwith software.

REFERENCES

Hassel 2012: Hassel et al. “Determination of VITA Classical shades withthe 3D-Master shade guide” Acta Odontol Scand. 2013; 71(3-4): 721-6.Dozic 2007: Dozic et al. “Performance of five commercially availabletooth color-measuring devices”, J Prosthodont. 2007; 16(2):93-100.

EMBODIMENTS

1. A method for determining shade of a patient's tooth, wherein themethod comprises:

-   -   obtaining a digital 3D representation of the tooth, where the        digital 3D representation comprises shape data and texture data        for the tooth; and    -   determining a tooth shade value for at least one point on the        tooth based on the texture data of the corresponding point of        the digital 3D representation and on known texture values of one        or more reference tooth shade values.        2. The method according to embodiment 1, wherein determining the        tooth shade value for the point comprises selecting the        reference tooth shade value with the known texture value closest        to the texture data of the point.        3. The method according to embodiment 1 or 2, wherein        determining the tooth shade value for the point comprises an        interpolation of the two or more reference tooth shade values        having known texture values close to the texture data of the        point.        4. The method according to any one of the preceding embodiments,        wherein the method comprises deriving a certainty score        expressing the certainty of the determined tooth shade value.        5. The method according to embodiment 4, wherein the method        comprises generating a visual representation of the certainty        score and displaying this visual representation in a user        interface.        6. The method according to embodiment 5, wherein the visual        representation of the certainty score is displayed together with        or is mapped onto the digital 3D representation of the tooth.        7. The method according to any one of embodiments 4 to 6,        wherein the method comprises comparing the derived certainty        score with a range of acceptable certainty score values.        8. The method according to any one of embodiments 4 to 7,        wherein the certainty measure relates to how uniform the        sub-scan texture information is at the point, and/or to how        close the texture data is to the known texture value of the        determined tooth shade value, and/or to the amount of texture        information used to derive the texture data at the point.        9. The method according to any one of embodiments 4 to 8,        wherein the visual representation of the certainty score        comprises a binary code, a bar structure with a color gradient,        a numerical value, and/or a comparison between the texture data        and the known texture value of the determined tooth shade value.        10. The method according to any one of the preceding        embodiments, wherein the one or more reference tooth shade        values relate to shade values for natural teeth with intact        surface and/or to shade values for teeth prepared for a dental        restoration.        11. The method according to any one of the preceding        embodiments, wherein the method comprises comparing the texture        data with known texture values for soft oral tissue, such as gum        tissue and gingiva.        12. The method according to any of the previous embodiments,        wherein the texture information comprises at least one of tooth        color or surface roughness.        13. The method according to any one of the preceding        embodiments, wherein the method comprises creating a shade        profile for the tooth from shade values determined one or more        points on the tooth.        14. The method according to embodiment 13, wherein the tooth        shade profile comprises a one or more tooth shade regions on the        tooth surface where an average tooth shade is derived for each        region from tooth shade values determined for a number of points        within the region        15. The method according to any of the previous embodiments,        wherein obtaining the digital 3D representation of the tooth        comprises recording a series of sub-scans of the tooth, where at        least one of said sub-scans comprises both texture information        and geometry information for said tooth, and generating the        digital 3D representation of the tooth from the recorded series        of sub-scans.        16. The method according to embodiment 15, wherein the texture        data at least partly are derived by combining the texture        information from corresponding parts of a number of the        sub-scans.        17. The method according to embodiment 16, wherein combining the        texture information from the sub-scans comprises interpolating        the texture information and/or calculating an average value of        the texture information.        18. The method according to embodiment 17, wherein the        calculated average value is a weighted average of the texture        information.        19. A user interface for determining and displaying shade of a        patient's tooth, wherein the user interface is configured for:    -   obtaining a digital 3D representation of the tooth, said digital        3D representation comprising shape data and texture data for the        tooth;    -   displaying at least the shape data of the digital 3D        representation such that the shape of the tooth is visualized in        the user interface;    -   determining a tooth shade value for at least one point on the        tooth based on the texture data of the corresponding point of        the digital 3D representation and on known texture values of one        or more reference tooth shade values; and displaying the        determined tooth shade value.

1. A computer-readable medium comprising one or more computer-executableinstructions that, when executed by at least one processor of acomputing device, cause the computing device to: obtaining a digital 3Drepresentation of the tooth based on scan data provided by an intraoralscanner, where the digital 3D representation comprises shape data andtexture data for the tooth; and determining a tooth shade value for atleast one point on the tooth based on the texture data of thecorresponding point of the digital 3D representation and on knowntexture values of one or more reference tooth shade values, wherein thecomputer-readable medium comprises deriving a certainty score expressingthe certainty of the determined tooth shade value.
 2. Thecomputer-readable medium according to claim 1, wherein determining thetooth shade value for the point comprises selecting the reference toothshade value with the known texture value closest to the texture data ofthe point.
 3. The computer-readable medium according to claim 1, whereindetermining the tooth shade value for the point comprises aninterpolation of the two or more reference tooth shade values havingknown texture values close to the texture data of the point.
 4. Thecomputer-readable medium according to claim 1, wherein the mediumcomprises generating a visual representation of the certainty score anddisplaying this visual representation in a user interface.
 5. Thecomputer-readable medium according to claim 4, wherein the visualrepresentation of the certainty score is displayed together with or ismapped onto the digital 3D representation of the tooth.
 6. Thecomputer-readable medium according to claim 1, wherein the certaintymeasure relates to how uniform the sub-scan texture information is atthe point, and/or to how close the texture data is to the known texturevalue of the determined tooth shade value, and/or to the amount oftexture information used to derive the texture data at the point.
 7. Thecomputer-readable medium according to claim 1, wherein thecomputer-readable medium comprises creating a shade profile for thetooth from shade values determined one or more points on the tooth.
 8. Acomputer-readable medium comprising one or more computer-executableinstructions that, when executed by at least one processor of acomputing device, cause the computing device to obtaining a digital 3Drepresentation of the tooth based on scan data provided by an intraoralscanner, where the digital 3D representation comprises shape data andtexture data for the tooth; and determining a tooth shade value for atleast one point on the tooth based on the texture data of thecorresponding point of the digital 3D representation and on knowntexture values of one or more reference tooth shade values, wherein themedium comprises creating a shade profile for the tooth from shadevalues determined one or more points on the tooth, and wherein the toothshade profile comprises a one or more tooth shade regions on the toothsurface where an average tooth shade is derived for each region fromtooth shade values determined for a number of points within the region.9. A computer-readable medium comprising one or more computer-executableinstructions that, when executed by at least one processor of acomputing device, cause the computing device to: obtaining a digital 3Drepresentation of the tooth based on scan data provided by an intraoralscanner, where the digital 3D representation comprises shape data andtexture data for the tooth; and determining a tooth shade value for atleast one point on the tooth based on the texture data of thecorresponding point of the digital 3D representation and on knowntexture values of one or more reference tooth shade values, whereinobtaining the digital 3D representation of the tooth comprises recordinga series of sub-scans of the tooth, where at least one of said sub-scanscomprises both texture information and geometry information for saidtooth, and generating the digital 3D representation of the tooth fromthe recorded series of sub-scans.
 10. The computer-readable mediumaccording to claim 9, wherein the texture data at least partly arederived by combining the texture information from corresponding parts ofa number of the sub-scans.
 11. The computer-readable medium according toclaim 10, wherein combining the texture information from the sub-scanscomprises interpolating the texture information and/or calculating anaverage value of the texture information.
 12. The computer-readablemedium according to claim 9, comprising determining an indicator that isvisualized next to the tooth shade value, and where the indicatorrepresents the reliability of the tooth shade value.
 13. Thecomputer-readable medium according to claim 9, comprising a userinterface, wherein the digital 3D representation is visualized on theuser interface, and the digital 3D representation includes patient'ssoft tissue, and if the point corresponds to the soft tissue a warningis visualized in the user interface.
 14. The computer-readable mediumaccording to claim 9, comprising a user interface, wherein the digital3D representation is visualized on the user interface, and the digital3D representation includes patient's soft tissue, and if the pointcorresponds to the soft tissue no shade value is indicated in the userinterface.
 15. A computer-readable medium comprising one or morecomputer-executable instructions that, when executed by at least oneprocessor of a computing device, cause the computing device to:obtaining a digital 3D representation of the tooth based on scan dataprovided by an intraoral scanner, where the digital 3D representationcomprises shape data and texture data for the tooth; and determining atooth shade value for at least one point on the tooth based on thetexture data of the corresponding point of the digital 3D representationand on known texture values of one or more reference tooth shade values,deriving an indicator representing a reliability of the tooth shadevalue, and displaying the indicator next to the tooth shade value.